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[NSE-642] Correctly get ResultAttrFromExpr for sql with 'case when IN/AND/OR' #638

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Dec 17, 2021
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[NSE-642] Correctly get ResultAttrFromExpr for sql with 'case when IN/AND/OR' #638

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3d1f73c
Fix issue in executing a sql with 'case when IN/AND'
PHILO-HE Dec 16, 2021
1ca0cb3
Cover 'case when OR'
PHILO-HE Dec 16, 2021
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14 changes: 10 additions & 4 deletions native-sql-engine/core/src/main/scala/com/intel/oap/expression/ConverterUtils.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -23,10 +23,12 @@ import java.nio.ByteBuffer
import java.util.ArrayList

import com.intel.oap.vectorized.ArrowWritableColumnVector
import org.apache.arrow.memory.ArrowBuf
import io.netty.buffer.{ByteBufAllocator, ByteBufOutputStream}
import org.apache.arrow.memory.ArrowBuf
import org.apache.arrow.flatbuf.MessageHeader
import org.apache.arrow.gandiva.evaluator._
import org.apache.arrow.gandiva.exceptions.GandivaException
import org.apache.arrow.gandiva.expression._
import org.apache.arrow.gandiva.expression.ExpressionTree
import org.apache.arrow.gandiva.ipc.GandivaTypes
import org.apache.arrow.gandiva.ipc.GandivaTypes.ExpressionList
Expand All @@ -35,8 +37,6 @@ import org.apache.arrow.vector._
import org.apache.arrow.vector.ipc.{ArrowStreamReader, ReadChannel, WriteChannel}
import org.apache.arrow.vector.ipc.message.{ArrowFieldNode, ArrowRecordBatch, IpcOption, MessageChannelReader, MessageResult, MessageSerializer}
import org.apache.arrow.vector.types.pojo.{ArrowType, Field, FieldType, Schema}
import org.apache.arrow.gandiva.expression._
import org.apache.arrow.gandiva.evaluator._

import org.apache.spark.internal.Logging
import org.apache.spark.sql.catalyst.expressions._
Expand All @@ -46,6 +46,7 @@ import org.apache.spark.sql.internal.SQLConf
import org.apache.spark.sql.types._
import org.apache.spark.sql.util.ArrowUtils
import org.apache.spark.sql.vectorized.{ColumnVector, ColumnarBatch}

import scala.collection.JavaConverters._
import scala.collection.mutable.ListBuffer

Expand All @@ -60,7 +61,6 @@ import org.apache.arrow.vector.types.TimeUnit
import org.apache.arrow.vector.types.pojo.ArrowType
import org.apache.arrow.vector.types.pojo.ArrowType.ArrowTypeID
import org.apache.arrow.vector.types.{DateUnit, FloatingPointPrecision}

import org.apache.spark.sql.catalyst.util.DateTimeConstants
import org.apache.spark.sql.catalyst.util.DateTimeConstants.MICROS_PER_SECOND
import org.apache.spark.sql.execution.datasources.v2.arrow.SparkSchemaUtils
Expand Down Expand Up @@ -387,6 +387,12 @@ object ConverterUtils extends Logging {
// for situation like: case when x = y
case cet: ColumnarEqualTo =>
new AttributeReference(name, cet.dataType, cet.nullable)()
case cin: ColumnarIn =>
new AttributeReference(name, cin.dataType, cin.nullable)()
case cand: ColumnarAnd =>
new AttributeReference(name, cand.dataType, cand.nullable)()
case cor: ColumnarOr =>
new AttributeReference(name, cor.dataType, cor.nullable)()
case other =>
val a = if (name != "None") {
new Alias(other, name)()
Expand Down